Time series · IBM
Granite TTM r2
Under 1M parameters: forecasting on a microcontroller budget.
Datasheet
Maker | IBM |
|---|---|
Parameters | 1 MVerifiedsafetensors.total from the HF API Source |
Licence | Apache-2.0Verified |
Access | Public download |
Task (HF pipeline) | time-series-forecasting |
First published on HF | 2024-10-08 |
Last updated on HF | 2025-02-26 |
Weights in memory | 0.0 GB at 16-bit · 0.0 GB at ~4.85 bitsEstimateParameters × bits ÷ 8. Excludes context cache and runtime overhead; not every model has a 4-bit build. |
Benchmark
1.02
GIFT-Eval MASE, geometric mean relative to seasonal naive (lower is better) · #7 of 7 scored in this category
Computed from TTM-R2-Pretrained: MASE 1.020, CRPS 0.873. config.json flags test-data leakage. Source
The description summarises the model card at https://huggingface.co/ibm-granite/granite-timeseries-ttm-r2. Parameters and licence are read from the Hugging Face API; the weights-in-memory line is our arithmetic, not a measurement.